docstr: Returns the learned model.
  
  :return: the learned model.
docstr_tok: ["Returns","the","learned","model",".",":","return",":","the","learned","model","."]
code: def get_model(self):
      """
      Returns the learned model.
  
      :return: the learned model.
      """
      state_refs = [w.get_state.remote() for w in self.remote_workers]
      state = ray.get(state_refs[0])
      return self._get_model_from_state(state)
  
imports: import itertools
  import logging
  import pickle
  import numpy
  import ray
  from zoo.common.utils import enable_multi_fs_load, enable_multi_fs_save
  from zoo.orca.data.ray_xshards import RayXShards
  from zoo.orca.learn.dl_cluster import RayDLCluster
  from zoo.orca.learn.tf2.tf_runner import TFRunner
  from zoo.orca.learn.ray_estimator import Estimator
  from zoo.orca.learn.utils import maybe_dataframe_to_xshards, dataframe_to_xshards, convert_predict_xshards_to_dataframe, update_predict_xshards, process_xshards_of_pandas_dataframe
  from zoo.orca.data.utils import process_spark_xshards
  from zoo.ray import RayContext
label_desc: Use image node_id 6 for calling the TensorFlow2Estimator obj's underlying member method code with example usage: obj.get_model() and returns: self